Artificial Intelligence Management: Foundations and Strategy

Understand AI Management at a Deep Level!

Business leaders see the promise of AI, but they are rarely given a look under the hood at the management mechanics necessary to sustain it. They are told AI will revolutionize their business, but rarely are they told how to manage thedata, the math, the metrics, and the messy realityof AI and data science.

Artificial Intelligence Managementis the definitive manual for the leader who is tired of soft explanations and ready for hard-hitting value. This book is a tactical blueprint for what an AI manager must do today. Unlike other books that stay away from in-depth analysis, this book doesn’t shy away from the complex managerial topics and dives into areas like the pitfalls of accuracy management, how “Shadow AI” bypasses traditional governance frameworks, how to hire and staff an AI team, and how to manage work breakdown structures.

Here are some of the topics and techniques that are covered:

· Build AI Team Talent: Use precise skill matrices to identify true builders and verify technical resumes.

· Start Investigating Agentic: Examine the potential and problems with using AI agents in your workplace.

· Investigate Generative AI: Delve into managing generative AI solutions.

· Master AI Metrics: Investigate key performance indicators to measure true model ROI.

· Govern Shadow AI: Secure your organization against unauthorized GenAI deployments and compliance risks.

· Manage the AI Lifecycle: Manage the AI Application development from data lineage to deployment.

· Neutralize Bias: Use data science innovation to improve decision-making.

· Navigate AI Regulation: Gain a clear roadmap for the EU AI Act, CCPA, and evolving global compliance.